Due to fast-paced technical development, companies are forced to modernise and update
their equipment, as well as production planning methods. In the ordering process, the customer
is interested not only in product specifications, but also in the manufacturing lead
time by which the product will be completed. Therefore, companies strive towards setting
an appealing but attainable manufacturing lead date.
Manufacturing lead time depends on many different factors; therefore, it is difficult to predict.
Estimation of manufacturing lead time is usually based on previous experience. In the
following research, manufacturing lead time for tools for aluminium extrusion was estimated
with Artificial Intelligence, more precisely, with Neural Networks.
The research is based on the following input data; number of cavities, tool type, tool category,
order type, number of orders in the last 3 days and tool diameter; while the only output
data are the number of working days that are needed to manufacture the tool. An Artificial
Neural Network (feed-forward neural network) was noted as a sufficiently accurate method
and, therefore, appropriate for implementation in the company.